SIS (0.8-3)

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Sure Independence Screening.

http://www.stat.columbia.edu/~yangfeng/pubs/jss1375.pdf
http://cran.r-project.org/web/packages/SIS

Variable selection techniques are essential tools for model selection and estimation in high-dimensional statistical models. Through this publicly available package, we provide a unified environment to carry out variable selection using iterative sure independence screening (SIS) and all of its variants in generalized linear models and the Cox proportional hazards model.

Maintainer: Yang Feng
Author(s): Jianqing Fan, Yang Feng, Diego Franco Saldana, Richard Samworth, Yichao Wu

License: GPL-2

Uses: glmnet, ncvreg, survival
Reverse depends: SparseLearner
Reverse suggests: SuperLearner

Released 5 months ago.


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